- 2.28.0 (latest)
 - 2.27.0
 - 2.26.0
 - 2.25.0
 - 2.24.0
 - 2.23.0
 - 2.22.0
 - 2.21.0
 - 2.20.0
 - 2.19.0
 - 2.18.0
 - 2.17.0
 - 2.16.0
 - 2.15.0
 - 2.14.0
 - 2.13.0
 - 2.12.0
 - 2.11.0
 - 2.10.0
 - 2.9.0
 - 2.8.0
 - 2.7.0
 - 2.6.0
 - 2.5.0
 - 2.4.0
 - 2.3.0
 - 2.2.0
 - 1.36.0
 - 1.35.0
 - 1.34.0
 - 1.33.0
 - 1.32.0
 - 1.31.0
 - 1.30.0
 - 1.29.0
 - 1.28.0
 - 1.27.0
 - 1.26.0
 - 1.25.0
 - 1.24.0
 - 1.22.0
 - 1.21.0
 - 1.20.0
 - 1.19.0
 - 1.18.0
 - 1.17.0
 - 1.16.0
 - 1.15.0
 - 1.14.0
 - 1.13.0
 - 1.12.0
 - 1.11.1
 - 1.10.0
 - 1.9.0
 - 1.8.0
 - 1.7.0
 - 1.6.0
 - 1.5.0
 - 1.4.0
 - 1.3.0
 - 1.2.0
 - 1.1.0
 - 1.0.0
 - 0.26.0
 - 0.25.0
 - 0.24.0
 - 0.23.0
 - 0.22.0
 - 0.21.0
 - 0.20.1
 - 0.19.2
 - 0.18.0
 - 0.17.0
 - 0.16.0
 - 0.15.0
 - 0.14.1
 - 0.13.0
 - 0.12.0
 - 0.11.0
 - 0.10.0
 - 0.9.0
 - 0.8.0
 - 0.7.0
 - 0.6.0
 - 0.5.0
 - 0.4.0
 - 0.3.0
 - 0.2.0
 
SamplingOptions(
    max_download_size: typing.Optional[int] = 500,
    enable_downsampling: bool = False,
    sampling_method: typing.Literal["head", "uniform"] = "uniform",
    random_state: typing.Optional[int] = None,
)Encapsulates the configuration for data sampling.
Attributes | 
      |
|---|---|
| Name | Description | 
max_download_size | 
        
          int, default 500
          Download size threshold in MB. If value set to None, the download size won't be checked.  | 
      
enable_downsampling | 
        
          bool, default False
          Whether to enable downsampling, If max_download_size is exceeded when downloading data (e.g., to_pandas()), the data will be downsampled if enable_downsampling is True, otherwise, an error will be raised.  | 
      
sampling_method | 
        
          str, default "uniform"
          Downsampling algorithms to be chosen from, the choices are: "head": This algorithm returns a portion of the data from the beginning. It is fast and requires minimal computations to perform the downsampling.; "uniform": This algorithm returns uniform random samples of the data.  | 
      
random_state | 
        
          int, default None
          The seed for the uniform downsampling algorithm. If provided, the uniform method may take longer to execute and require more computation.  | 
      
Methods
with_disabled
with_disabled() -> bigframes._config.sampling_options.SamplingOptionsConfigures whether to disable downsampling
| Returns | |
|---|---|
| Type | Description | 
bigframes._config.sampling_options.SamplingOptions | 
        The configuration for data sampling. | 
with_max_download_size
with_max_download_size(
    max_rows: typing.Optional[int],
) -> bigframes._config.sampling_options.SamplingOptionsConfigures the maximum download size for data sampling in MB
| Parameter | |
|---|---|
| Name | Description | 
max_rows | 
        
          None or int
          An int value for the maximum row size.  | 
      
| Returns | |
|---|---|
| Type | Description | 
bigframes._config.sampling_options.SamplingOptions | 
        The configuration for data sampling. | 
with_method
with_method(
    method: typing.Literal["head", "uniform"],
) -> bigframes._config.sampling_options.SamplingOptionsConfigures the downsampling algorithms to be chosen from
| Parameter | |
|---|---|
| Name | Description | 
method | 
        
          None or Literal
          A literal string value of either head or uniform data sampling method.  | 
      
| Returns | |
|---|---|
| Type | Description | 
bigframes._config.sampling_options.SamplingOptions | 
        The configuration for data sampling. | 
with_random_state
with_random_state(
    state: typing.Optional[int],
) -> bigframes._config.sampling_options.SamplingOptionsConfigures the seed for the uniform downsampling algorithm
| Parameter | |
|---|---|
| Name | Description | 
state | 
        
          None or int
          An int value for the data sampling random state  | 
      
| Returns | |
|---|---|
| Type | Description | 
bigframes._config.sampling_options.SamplingOptions | 
        The configuration for data sampling. |